Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality

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dc.creatorMurata, Masaki
dc.creatorUchimoto, Kiyotaka
dc.creatorMa, Qing
dc.creatorIsahara, Hitoshi
dc.date2001-12-05
dc.date.accessioned2026-07-07T03:18:00Z
dc.date.available2026-07-07T03:18:00Z
dc.descriptionThis paper describes experiments carried out using a variety of machine-learning methods, including the k-nearest neighborhood method that was used in a previous study, for the translation of tense, aspect, and modality. It was found that the support-vector machine method was the most precise of all the methods tested.
dc.description8 pages. Computation and Language
dc.identifierhttps://arxiv.org/abs/cs/0112003
dc.identifierhttp://arxiv.org/abs/cs/0112003
dc.identifierACL Workshop, the Data-Driven Machine Translation, 2001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30939
dc.subjectComputation and Language
dc.subjectH.3.3; I.2.7
dc.titleUsing a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality
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